code: def test_train_test_split():
      train = load_dataset(train=True, object_type="VisionData")
      test = load_dataset(train=False, object_type="VisionData")
  
      for batch in train:
          batch = BatchWrapper(
              batch, train.task_type, train.number_of_images_cached
          )
          train.update_cache(
              len(batch), batch.numpy_labels, batch.numpy_predictions
          )
  
      for batch in test:
          batch = BatchWrapper(
              batch, test.task_type, test.number_of_images_cached
          )
          test.update_cache(
              len(batch), batch.numpy_labels, batch.numpy_predictions
          )
  
      assert_that(
          train.number_of_images_cached + test.number_of_images_cached,
          equal_to(128),
      )
      assert_that(
          train.get_observed_classes(),
          is_not(equal_to(test.get_observed_classes())),
      )
  
file_path: deepchecks/tests/vision/datasets/test_coco_tensorflow.py
imports: import tensorflow
  from hamcrest import assert_that, calling, equal_to, instance_of, is_not, raises
  from deepchecks.vision import VisionData
  from deepchecks.vision.datasets.detection.coco_tensorflow import load_dataset
  from deepchecks.vision.datasets.detection.coco_utils import COCO_DIR
  from deepchecks.vision.vision_data.batch_wrapper import BatchWrapper
label_desc: Use image node_id 4 for calling a global function with example usage: test_train_test_split() without return types